Re: st: re: tsset with non-integers

If the errors are dependent then observations must be clustered by
definition (hence the need to tsset). Perhaps you are looking to test
something else?

Clustering can be, for example, a repeated measure on an individual, or
hierarchically nested observations (i.e., individuals in firms)--that is
what you are looking at then set the panel variable as firm, i.e., "iis
firm".

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Hi Eva,
The way I understood Kit's response was that both suggested approaches (estat bgodfrey and wntestq) require the user to tsset the data, which I cannot do. I am looking to test the autocorrelation of residuals terms so that I can check the regression assumption of indepence of errors. Thank you.
Best,
Frank

Frank,
please tell us what you don't understand about the replies you have
got so far. Kit gave recommendations for testing for autocorrelation
in residuals. If it is serial correlation that you are after, you have
time series (or panel) data, and should tell Stata about it, using the
-tsset- command. See -help tsset-.
If it is not serial correlation but some other kind of dependence, you
need to be more specific about the type of data you have.
Kit discouraged the use of -durbinh-, but if you insist on using it
anyway, you need to -tsset- your data first. In any case, residuals
are very unlikely to be integers. Your _time_ variable (e.g. years or
quarters or months) could be integer. But that has nothing to do with
your residuals.
Eva
2009/5/7 Frank Gallo <fjgallo@mac.com>:

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Hi Nick & Kit,
Thank you for your responses. My goal is only to check the independence of residual terms following a regression run. My reading of the durbinh command lead me to believe that it would help me achieve my goal. Can you suggest an alternative option to check the independence of residual terms that are non-integers? Thank you.
Best,
Frank
On Thursday, May 07, 2009, at 06:32AM, "Kit Baum" <baum@bc.edu> wrote:

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Frank said
What I would like to do, which I cannot find exactly in the archives,
is to check the independence of the residual terms (e) from a
regression. I would like to run the -durbinh- command...
Nick Cox answered the technical question re -tsset-. I do not
recommend you rely on the -durbinh- command. It is a special case of
the Breusch-Godfrey test in which you only consider AR(1) vs i.i.d.
The -estat bgodfrey- postestimation command allows you to test for
higher-order autocorrelation as well (which might well be present even
if an AR(1) coefficient is insignificant). Also consider using -
wntestq-, which is an unconditional test of the residuals'
autocorrelation function. (B-G is a conditional test in that it uses
the X matrix from the regression, whereas the Lung-Box-Pierce "Q" test
may be applied to any time series). All will require that the data are
properly -tsset-.
Kit
Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html
An Introduction to Stata Programming
| http://www.stata-press.com/books/isp.html
An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html